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[version] support transformers 449 (#6982)
* support transformers 449 * fix mm plugin Former-commit-id: b00b290c07beb560a5af857ce64f4ce424831a2c
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@ -390,7 +390,7 @@ huggingface-cli login
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| ------------ | ------- | --------- |
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| python | 3.9 | 3.10 |
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| torch | 1.13.1 | 2.4.0 |
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| transformers | 4.41.2 | 4.45.2 |
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| transformers | 4.41.2 | 4.49.0 |
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| datasets | 2.16.0 | 3.2.0 |
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| accelerate | 0.34.0 | 1.2.1 |
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| peft | 0.11.1 | 0.12.0 |
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@ -399,9 +399,9 @@ huggingface-cli login
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| Optional | Minimum | Recommend |
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| ------------ | ------- | --------- |
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| CUDA | 11.6 | 12.2 |
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| deepspeed | 0.10.0 | 0.14.0 |
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| deepspeed | 0.10.0 | 0.16.2 |
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| bitsandbytes | 0.39.0 | 0.43.1 |
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| vllm | 0.4.3 | 0.6.6 |
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| vllm | 0.4.3 | 0.7.2 |
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| flash-attn | 2.3.0 | 2.7.2 |
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### Hardware Requirement
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@ -392,7 +392,7 @@ huggingface-cli login
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| ------------ | ------- | --------- |
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| python | 3.9 | 3.10 |
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| torch | 1.13.1 | 2.4.0 |
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| transformers | 4.41.2 | 4.45.2 |
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| transformers | 4.41.2 | 4.49.0 |
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| datasets | 2.16.0 | 3.2.0 |
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| accelerate | 0.34.0 | 1.2.1 |
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| peft | 0.11.1 | 0.12.0 |
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@ -401,9 +401,9 @@ huggingface-cli login
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| 可选项 | 至少 | 推荐 |
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| ------------ | ------- | --------- |
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| CUDA | 11.6 | 12.2 |
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| deepspeed | 0.10.0 | 0.14.0 |
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| deepspeed | 0.10.0 | 0.16.2 |
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| bitsandbytes | 0.39.0 | 0.43.1 |
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| vllm | 0.4.3 | 0.6.6 |
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| vllm | 0.4.3 | 0.7.2 |
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| flash-attn | 2.3.0 | 2.7.2 |
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### 硬件依赖
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@ -1,5 +1,5 @@
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transformers>=4.41.2,<=4.48.3,!=4.46.*,!=4.47.*,!=4.48.0,!=4.48.1,!=4.48.2;python_version<'3.10'
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transformers>=4.41.2,<=4.48.3,!=4.46.*,!=4.47.*,!=4.48.0;python_version>='3.10'
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transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.*;python_version<'3.10'
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transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.0;python_version>='3.10'
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datasets>=2.16.0,<=3.2.0
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accelerate>=0.34.0,<=1.2.1
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peft>=0.11.1,<=0.12.0
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@ -20,7 +20,7 @@ Level:
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Dependency graph:
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main:
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transformers>=4.41.2,<=4.48.3,!=4.46.*,!=4.47.*,!=4.48.0
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transformers>=4.41.2,<=4.49.0,!=4.46.*,!=4.47.*,!=4.48.0
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datasets>=2.16.0,<=3.2.0
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accelerate>=0.34.0,<=1.2.1
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peft>=0.11.1,<=0.12.0
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@ -187,8 +187,6 @@ class MultiModalDataCollatorForSeq2Seq(DataCollatorForSeq2Seq):
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mm_inputs["cross_attention_mask"] = F.pad(cross_attention_mask, (0, 0, 0, 0, 0, seq_len - orig_len))
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features.update(mm_inputs)
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if isinstance(features.get("pixel_values"), list): # for pixtral inputs
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features = features.data # use default_collate() instead of BatchEncoding.to()
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if "image_bound" in features: # for minicpmv inputs
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bsz, seq_length = features["input_ids"].shape
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@ -380,10 +380,8 @@ class LlavaNextPlugin(BasePlugin):
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num_image_tokens = 0
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messages = deepcopy(messages)
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mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
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if "image_sizes" in mm_inputs:
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image_sizes = iter(mm_inputs["image_sizes"])
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if "pixel_values" in mm_inputs:
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image_sizes = iter(mm_inputs["image_sizes"].tolist())
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height, width = get_image_size(to_numpy_array(mm_inputs["pixel_values"][0][0]))
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for message in messages:
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@ -439,7 +437,7 @@ class LlavaNextVideoPlugin(BasePlugin):
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messages = deepcopy(messages)
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mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
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if "pixel_values" in mm_inputs:
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image_sizes = iter(mm_inputs["image_sizes"])
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image_sizes = iter(mm_inputs["image_sizes"].tolist())
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height, width = get_image_size(to_numpy_array(mm_inputs["pixel_values"][0][0]))
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for message in messages:
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content = message["content"]
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@ -916,16 +914,14 @@ class PixtralPlugin(BasePlugin):
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num_image_tokens = 0
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messages = deepcopy(messages)
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mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
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image_input_sizes = mm_inputs.get("image_sizes", None)
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if "pixel_values" in mm_inputs:
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image_sizes = iter(mm_inputs["image_sizes"].tolist())
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for message in messages:
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content = message["content"]
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while IMAGE_PLACEHOLDER in content:
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if image_input_sizes is None:
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raise ValueError("Cannot get image input sizes.")
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if self.expand_mm_tokens:
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image_size = image_input_sizes[0][num_image_tokens]
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height, width = image_size
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height, width = next(image_sizes)
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num_height_tokens = height // patch_size
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num_width_tokens = width // patch_size
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replace_tokens = [[image_token] * num_width_tokens + [image_break_token]] * num_height_tokens
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@ -959,9 +955,6 @@ class PixtralPlugin(BasePlugin):
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) -> Dict[str, Union[List[int], "torch.Tensor"]]:
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self._validate_input(images, videos, audios)
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mm_inputs = self._get_mm_inputs(images, videos, audios, processor)
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if mm_inputs.get("pixel_values"):
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mm_inputs["pixel_values"] = mm_inputs["pixel_values"][0]
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mm_inputs.pop("image_sizes", None)
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return mm_inputs
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@ -94,7 +94,7 @@ def check_dependencies() -> None:
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r"""
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Checks the version of the required packages.
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"""
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check_version("transformers>=4.41.2,<=4.48.3,!=4.46.0,!=4.46.1,!=4.46.2,!=4.46.3,!=4.47.0,!=4.47.1,!=4.48.0")
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check_version("transformers>=4.41.2,<=4.49.0,!=4.46.0,!=4.46.1,!=4.46.2,!=4.46.3,!=4.47.0,!=4.47.1,!=4.48.0")
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check_version("datasets>=2.16.0,<=3.2.0")
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check_version("accelerate>=0.34.0,<=1.2.1")
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check_version("peft>=0.11.1,<=0.12.0")
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